The authors in [1]} propose another deep CNN model, CoroNet, to detect COVID-19 infection from chest X-ray images automatically. The foundation of Coro-Net is on Xception architecture, which is pre-trained on ImageNet and then trained on a combined dataset prepared using two publicly available datasets. The dataset used to train Coro-Net comprises 1300 images that achieve an overall accuracy of 89.6%. Although Coro-Net shows promising results on a small dataset, its efficiency can be increased by using a large dataset and minimum pre-processing of data.
